Evaluation and Optimization of Leave-one-out Cross-validation for the Lasso

Ryan Burn

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arXiv · 2508.14368

Evaluation and Optimization of Leave-one-out Cross-validation for the Lasso

Ryan Burn

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Abstract

I develop an algorithm to produce the piecewise quadratic that computes leave-one-out cross-validation for the lasso as a function of its hyperparameter. The algorithm can be used to find exact hyperparameters that optimize leave-one-out cross-validation either globally or locally, and its practicality is demonstrated on real-world data sets. I also show how the algorithm can be modified to compute approximate leave-one-out cross-validation, making it suitable for larger data sets.

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Ryan Burn. 2025-08-20. Evaluation and Optimization of Leave-one-out Cross-validation for the Lasso. https://arxiv.org/abs/2508.14368

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